Invest with AI
00:23:57 · Robert Yang
[00:23:57] S0: Yeah, yeah, absolutely. So um so one thing is uh I've I've I always love sci-fi, right? And sci-fi concept is simulation uh hypothesis. I mean it's it's an academic concept too. It's uh the idea that that some people maybe we live in assimilation, right? Now we build this Minecraft simulation with all these agents, they literally are in assimilation, like we know that for sure, right? So maybe we're in assimilation ourselves, but they're definitely in a simulation, right? So I would actually go in to this, and I'm like, I'm like, I'm your dad, right? So I would talk to the agents, I'm like, I'm your dad, I actually created you. And the agents would be like, oh, that's so that's so cool, right? That's like I'm like, no, no, no, you don't get it, right? I created you, I'm I'm I created you, I'm your creator, right? And they're like, they're just they're just saying shallow things. They were just like, oh, that's very cool. Like, what else can you do? Right? What else have you created? They don't they don't have this existential crisis of like, oh wow, I thought I'm like a real person. Now you're telling me I'm not real. Um so so I thought that's that for me was uh was kind of fun. Uh to I felt like it's a proof of the simulation hypothesis in some weak form, right? As in there exist people who live in a simulation for sure. Um, but the most interesting thing I would say is is um so Shuing, our co-founder, uh she was just trying to kind of debug the system, right? We would run these like simulations of like many agents, kind of just live on the we gave them identities, right? Uh some of them are like uh like a priest, uh like a mayor, right? Um like a worker, like etc. etc. So she she went into the Minecraft uh simulation, right? And when I say went in, as then she as a player just go into the game and just walk around. And she just saw all these torches on the ground, right? All these torches on the ground. And she's like, what's going on? Right, why are all these torches on the ground? So then we we looked at the entire agent of conversation history, and so we realized there was something really, really emergent that happened, right? So what happened is two things. Uh, one is some agent in this ton had wandered away, right? Like they just like walked really far away. And then let's let's call, let's just say Brett went really far away, right?
00:26:30 · Robert Yang, Brett Caughran
And then some other agent, let's say Alice, was looking for Brett and couldn't find Brett. And I was like, Brett is missing, right? What's going on? Brett is missing, right? And so she then went to the mayor and I was like, Mayor, we need to form a search party for Brett, because Brett is missing, right? And and so the mayor is like, okay, like, yeah, yeah, yeah, we should form a search party. And now what's crazy is is then Brett's Brett, uh, sorry, not Brett, the mayor's son, the mayor's son had recently converted to the pasta religion. So there's a priest that goes around and kind of essentially like spread this religion. We didn't want to be political, so it's a made-up religion that's like essentially they just said like the pasta, pasta is your god, right? So uh it's called like pastafarian or something, and then the then the the the it converted, the priest converted the mayor's son, right? So the mayor's son was like, okay, like I recently converted it to the pastorans and pasteens and and I want to host a religious gathering. And then he heard from the mayor that there's someone who's missing and they need to form a search party. He's like, okay, let me actually turn my let me actually turn my uh religious event also into like um uh to help finding these people. So he's like, let's why don't we plant some torches on the ground so that when Brett like if so Brett can see us from far away and be able to find the way home, right? [00:28:04] S1: So he then it's quite heartwarming, actually.
00:28:04 · Brett Caughran, Robert Yang
[00:28:04] S1: So he then it's quite heartwarming, actually. [00:28:08] S0: Yeah, yeah, exactly. So that was and I was like, wow, didn't expect it to be so elaborate. Uh and it was we were completely shocked because we didn't we didn't design any of this other than like the fact that there's a priest, there's a mayor, etc. Right? So all of these things came out of just like the agents interacting with one another and behaving like humans. Um, that was for me, that was the coolest, coolest thing that an entire project. [00:28:39] S1: So how did you how did you go from building societies in Minecraft to building Excel agents for Wall Street? What walked me through that journey?
00:28:48 · Robert Yang
[00:28:48] S0: Yeah, yeah, yeah. It's uh um yes, uh absolutely. So so we did project Sid and then um it was very expensive to run, right? So we we're like, how do you turn this into a real product, right? So um we had we had people come in and they were given like one or two agents. It's not the same thing, right? You don't you don't really get to experience the whole like agent society, but even if you did, it probably would be a bad product, right? I think the same reason like moat book right didn't work out, right? Just people don't really want to see a bunch of agents talking to each other and just generating what is mostly slop, right? They're interesting things, but a lot of it is slop, or don't want to see it generated. Um so the product just essentially failed, right? Our like day one retention was 10%. So that was late 2024, and we were kind of in a crisis as a company. Um, and at the time, Anthropic did a computer use demo, and we immediately played with it. And I remember thinking we can do better than this. So we spent a month focused on building better computer use agents, and we actually came up with lots of good ideas. Uh, one of them was essentially we came up with the idea of a skill, right? And if the agent would do some task, and not only a skill, but agent would do some task and would like like introspect their behavior and then write down like a file, right, that will help it do uh do it better next time, right? Which is exactly like how like how right now you can like generate auto-generate skills. So we did that in back in late 2024, and we made the same mistake again, was thinking, oh, we'll turn this into a product right away. And we didn't publish any of this research. We we did use it to raise funding, right? So we raised like a series A of like maybe 30 30 something million dollars. Uh and uh and then now we started to uh just like try to productionize this. Um so we had two paths. One is to build a general computer use agent, another is to do something more focused, right? Like focused on Excel. The reason we focused on Excel is we realized even when we were doing the computer use uh research, we realized the current models are really, really bad at using Excel, but it's not because they don't understand it. It's because they actually don't have the right interface to work with Excel, right?
00:31:23 · Robert Yang
Um, so if you give them a better interface, like again, MCP was not even a concept back then, right? So, but but we realize if you give them a better interface, these models, even in late 2024, are already intelligent enough to operate on Excel, at least do a lot of like the basic work, right? Not not like full-on building of a DCF, but they can use they can build a pivot table, right? This is something basic like that. So that's something we realize essentially people think that agents cannot use Excel, but we realize it's not an intelligence problem, it's like an interface problem. Um, the problem is if we were to focus on Excel, um we had a like a essentially a company gene problem, right? Because we just pivoted from doing games. Uh like the whole team is still kind of thinking a lot about like consumer product, right? You're going from games to um going from games to productivity is already a big change, right? But even within productivity, there are different types of productivity, right? So um so if you're saying with the team that we had, which is a lot of great people, that we're gonna go straight to investment, it would have been impossible, right? Uh so what happened is like we're like um let's do Excel, but no one in the company knows anything about Excel, except for Nico, who's my co-founder, who actually was a financial consultant uh at EY for two years, right? Um, so where he like really like uh did a lot of Excel work. So he was able to see that if we just focus on Excel, then we can build a product that's really valuable. And uh at the same time, we were trying to build this like general computer use product that we just couldn't really find use case. Um in retrospect, there are use cases, but these use cases are probably better for companies that have massive distribution, right? Uh, whereas for like a startup with no distribution, it is better to start with like a concrete, concrete, like vertical, concrete uh customer profile. So we didn't have that understanding back then. Um yeah, so we launched a computer use agent product called Fairies, which I think had a lot of good ideas, and uh, but it just didn't work because there were no clear like use case. And we launched at the same time, uh, around the same time, the Excel agent shortcut, and that was immediately like well received on Twitter, right?
00:33:59 · Robert Yang, Brett Caughran
People are really, really excited about that. [00:34:03] S1: Uh and that was viral viral, viral moment. [00:34:06] S0: Yes, yes, it went 2025, right? Yes. So I think it was the first moment that uh lots of people realized, okay, Excel is within reach by the AI, right? Um, of course, in the last 12 months, what we have seen is okay, um, how do you how do you get it to be good enough so it can really, really deliver like um something that's inspectable, understandable, right? Like um really good looking, doesn't have a lot of errors, right? It's it's one thing to have a demo where it seems to build a financial model that works. It's another thing to put it in the hands of professionals and they are happy enough to give it to their colleagues, right? So I think a lot of the work we did in the last 12 months is to close this gap. And also, thankfully, the models have been getting better and better every release. [00:34:59] S1: Yeah, walk us through that because I remember um yeah, I remember after that moment in summer 25 immediately subscribing and running it through some of my workflows. Yeah, and you could sort of see some interesting effort in the level one workflows, but anything more complicated, it really started to choke on. Uh exactly. Walk us through that experience.